Vehicle Radar Sensor Utilizing Non-Uniform Frequency Modulated Continuous Wave (FMCW) Chirps

ABSTRACT

A vehicle radar sensor utilizes Frequency Modulated Continuous Wave (FMCW) radar signals that incorporate non-uniform FMCW chirps having chirp profiles that differ from one another to sense one or more parameters of one or more objects in a field of view of the radar sensor. The chirp profiles may differ from one another in various manners, e.g., based on starting frequency, repetition interval, duration and/or slope, and among other advantages, may be used to enhance sensing of various parameters such as range, Doppler/velocity and/or angle.

BACKGROUND

As computing and vehicular technologies continue to evolve,autonomy-related features have become more powerful and widelyavailable, and capable of controlling vehicles in a wider variety ofcircumstances. For automobiles, for example, the automotive industry hasgenerally adopted SAE International standard J3016, which designates 6levels of autonomy. A vehicle with no autonomy is designated as Level 0,and with Level 1 autonomy, a vehicle controls steering or speed (but notboth), leaving the operator to perform most vehicle functions. WithLevel 2 autonomy, a vehicle is capable of controlling steering, speedand braking in limited circumstances (e.g., while traveling along ahighway), but the operator is still required to remain alert and beready to take over operation at any instant, as well as to handle anymaneuvers such as changing lanes or turning. Starting with Level 3autonomy, a vehicle can manage most operating variables, includingmonitoring the surrounding environment, but an operator is stillrequired to remain alert and take over whenever a scenario the vehicleis unable to handle is encountered. Level 4 autonomy provides an abilityto operate without operator input, but only in specific conditions suchas only certain types of roads (e.g., highways) or only certaingeographical areas (e.g., specific cities for which adequate mappingdata exists). Finally, Level 5 autonomy represents a level of autonomywhere a vehicle is capable of operating free of operator control underany circumstances where a human operator could also operate.

The fundamental challenges of any autonomy-related technology relate tocollecting and interpreting information about a vehicle's surroundingenvironment, along with making and implementing decisions toappropriately control the vehicle given the current environment withinwhich the vehicle is operating. Therefore, continuing efforts are beingmade to improve each of these aspects, and by doing so, autonomousvehicles increasingly are able to reliably handle a wider variety ofsituations and accommodate both expected and unexpected conditionswithin an environment.

One particular technology that is increasingly relied upon forcollecting information about a vehicle's surrounding environment isradar, which is based on the emission, reflection and sensing of radiowave electromagnetic radiation within an environment to detect, and insome instances, determine the position and/or velocity of, variousobjects (also sometimes referred to as targets) within the environment.Despite continuing improvements to radar performance, however, both costand technical limitations continue to exist, so a continuing need existsfor improvements to radar technology, and particularly for radartechnology used in connection with the control of an autonomous vehicle.

Some radar sensors used in automotive applications, for example, rely onFrequency Modulated Continuous Wave (FMCW) radar signals where a frameof “chirps” is emitted by a radar transmitter and sensed by a radarreceiver in order to determine the position and/or velocity of variousobjects within an environment. The chirps generated by a radartransmitter generally have the same chirp profile, e.g., with the samestarting frequency, the same duration, the same repetition interval andthe same slope, and the configuration of the chirp profile, with apractically limited analog to digital conversion (ADC) sampling rate,can greatly impact the maximum range, the maximum unambiguous velocity,the responsiveness and the resolution of the radar sensor. Furthercomplicating radar sensor performance are the inherent limitations ofanalog to digital conversion (ADC), as the sampling rate of an ADCcircuit can also impact these various performance parameters. As aresult, tradeoffs are often required to be made in order to balanceappropriate range, velocity, responsiveness, and resolution capabilitiesof a radar sensor.

SUMMARY

The present disclosure is generally related to a vehicle radar sensorthat utilizes Frequency Modulated Continuous Wave (FMCW) radar signalsthat incorporate non-uniform FMCW chirps having chirp profiles thatdiffer from one another to sense one or more parameters of one or moreobjects in a field of view of the radar sensor. The chirp profiles maydiffer from one another in various manners, e.g., based on startingfrequency, repetition interval, duration and/or slope, and among otheradvantages, may be used to enhance sensing of various parameters such asrange, Doppler/velocity and/or angle.

Therefore, consistent with one aspect of the invention, a radar sensorfor a vehicle may include a radar transmitter configured to transmit afirst radar signal, the first radar signal including a frame associatedwith a plurality of frequency modulated continuous wave (FMCW) chirps,where at least a subset of the plurality of FMWC chirps are non-uniformFMCW chirps having chirp profiles that differ from one another, a radarreceiver configured to receive a second radar signal that is a reflectedsignal of the first radar signal, and control logic coupled to the radarreceiver and configured to process the second radar signal, based on thenon-uniform FMCW chirps in the frame, to sense one or more parameters ofan object in a field of view of the radar transmitter.

In some embodiments, the chirp profiles of the FMCW chirps differ basedupon starting frequency. Also, in some embodiments, the chirp profilesof the FMCW chirps differ based upon repetition interval. Further, insome embodiments, the chirp profiles of the FMCW chirps differ basedupon chirp duration. In some embodiments, the chirp profiles of the FMCWchirps differ based upon chirp slope.

In addition, in some embodiments, the frame further includes a pluralityof uniform FMCW chirps having a substantially same chirp profile. Insome embodiments, the at least a subset of the plurality of FMWC chirpsincludes a plurality of non-uniform FMCW chirps having chirp profilesthat differ from one another, and the plurality of uniform FMCW chirpsand the plurality of non-uniform FMCW chirps are interleaved with oneanother.

In addition, in some embodiments, the control logic is configured toprocess the second radar signal to sense one or more parameters of aplurality of objects in a field of view of the radar transmitter, thechirp profiles of the FMCW chirps differ based upon starting frequencyand repetition interval, and the control logic uses the non-uniform FMCWchirps in the frame to sense the one or more parameters of the pluralityof objects by performing a range transformation with fast-time samplesof the second radar signal to generate a coarse resolution data cubeincluding coarse resolution range parameters for the plurality ofobjects and arranged in a plurality of range bins in a fast-timedimension, upsampling the generated coarse resolution data cube alongthe fast-time dimension to generate an upsampled data cube, compensatingfor phase variations due to starting frequency variations in thenon-uniform FMCW chirps along a slow-time dimension of the upsampleddata cube for each of the plurality of range bins to enhance rangeresolution in the upsampled data cube, and performing a Dopplertransformation on the upsampled data cube based upon starting frequencyand repetition interval variations in the non-uniform FMCW chirps togenerate Doppler parameters for the plurality of objects. Moreover, insome embodiments, the range transformation includes a Fast FourierTransform (FFT) transformation and the Doppler transformation includes aDiscrete Fourier Transform (DFT) transformation.

In some embodiments, the chirp profiles of the FMCW chirps differ basedupon starting frequency and repetition interval, the frame furtherincludes a plurality of uniform FMCW chirps having a substantially samechirp profile, and the control logic uses the non-uniform FMCW chirps inthe frame to sense the one or more parameters of the object bygenerating a uniform data cube by performing a range transformation withfast-time samples of the second radar signal and using the uniform FMCWchirps, and detecting a plurality of candidate objects in the uniformdata cube. Moreover, in some embodiments, the control logic further usesthe non-uniform FMCW chirps in the frame to sense the one or moreparameters of the object by generating a non-uniform data cube byperforming a range transformation with fast-time samples of the secondradar signal and using the non-uniform FMCW chirps, and enhancing rangeresolution for at least a subset of the plurality of candidate objectsusing the non-uniform data cube.

In some embodiments, the control logic further uses the non-uniform FMCWchirps in the frame to sense the one or more parameters of the object bygenerating a non-uniform data cube by performing a range transformationwith fast-time samples of the second radar signal and using thenon-uniform FMCW chirps, and performing a Doppler transformation withthe non-uniform data cube to resolve Doppler ambiguity in at least asubset of the plurality of candidate objects. In addition, in someembodiments, the control logic further uses the non-uniform FMCW chirpsin the frame to sense the one or more parameters of the object byperforming a Doppler transformation with the uniform data cube togenerate Doppler parameters for the plurality of candidate objects,where performing the Doppler transformation with the uniform data cubeintroduces Doppler ambiguity in the uniform data cube, and performingthe Doppler transformation with the non-uniform data cube resolves theDoppler ambiguity introduced in the uniform data cube. In someembodiments, the Doppler transformation performed with the uniform datacube includes a Fast Fourier Transform (FFT) transformation and theDoppler transformation performed with the non-uniform data cube includesa Discrete Fourier Transform (DFT) transformation.

Moreover, in some embodiments, the control logic further uses thenon-uniform FMCW chirps in the frame to sense the one or more parametersof the object by generating a non-uniform data cube by performing arange transformation with fast-time samples of the second radar signaland using the non-uniform FMCW chirps, and performing a beamformingtransformation with the non-uniform data cube to resolve angle ambiguityin at least a subset of the plurality of candidate objects in theuniform data cube. Also, in some embodiments, the control logic furtheruses the non-uniform FMCW chirps in the frame to sense the one or moreparameters of the object by performing a beamforming transformation withthe uniform data cube to generate angle parameters for the plurality ofcandidate objects, where performing the beamforming transformation withthe uniform data cube introduces angle ambiguity in the uniform datacube, and performing the beamforming transformation with the non-uniformdata cube resolves the angle ambiguity introduced in the uniform datacube. In some embodiments, the beamforming transformation performed withthe uniform data cube includes a Fast Fourier Transform (FFT)transformation and the beamforming transformation performed with thenon-uniform data cube includes a Discrete Fourier Transform (DFT)transformation.

In addition, in some embodiments, the radar transmitter is a multipleinput multiple output (MIMO) radar transmitter including a plurality oftransmit channels and the radar receiver is a MIMO radar receiverincluding a plurality of receive channels, the first radar signal isgenerated for a first transmit channel of the plurality of transmitchannels and the second radar signal is received by a first receivechannel of the plurality of receive channels, the range transformationperformed using the uniform FMCW chirps and the range transformationperformed using the non-uniform FMCW chirps are performed concurrently,and the control logic is further configured to perform MIMO demodulationprior to generating the uniform and non-uniform data cubes. Also, insome embodiments, the chirp profiles of the FMCW chirps differ basedupon starting frequency such that a total frequency band of the frame issplit into a plurality of sub-bands defined by the plurality ofnon-uniform FMCW chirps, and the control logic uses the non-uniform FMCWchirps in the frame to sense the one or more parameters of the object bysubsampling on range within the total frequency band of the frame.

Moreover, in some embodiments, the chirp profiles of the FMCW chirpsdiffer based upon starting frequency and repetition interval, and thecontrol logic uses the non-uniform FMCW chirps in the frame to sense theone or more parameters of the object by subsampling on Doppler over aduration of the frame. Further, in some embodiments, the chirp profilesof the FMCW chirps differ based upon starting frequency and repetitioninterval, the radar transmitter is a multiple input multiple output(MIMO) radar transmitter including a plurality of transmit channels andthe radar receiver is a MIMO radar receiver including a plurality ofreceive channels, the first radar signal is generated for a firsttransmit channel of the plurality of transmit channels and the secondradar signal is received by a first receive channel of the plurality ofreceive channels, and the control logic uses the non-uniform FMCW chirpsin the frame to sense the one or more parameters of the object bysubsampling over an aperture of the MIMO radar receiver.

Consistent with another aspect of the invention, a radar sensor for avehicle may include a radar transmitter configured to transmit a firstradar signal, and control logic coupled to the radar transmitter andconfigured to control the radar transmitter to generate the first radarsignal to include a frame that includes a plurality of frequencymodulated continuous wave (FMCW) chirps, where at least a subset of theplurality of FMCW chirps are non-uniform FMCW chirps having chirpprofiles that differ from one another.

Consistent with another aspect of the invention, a radar sensor for avehicle may include a radar receiver configured to receive a secondradar signal that is a reflected signal of a first radar signal, thefirst radar signal including a frame associated with a plurality offrequency modulated continuous wave (FMCW) chirps, where at least asubset of the plurality of FMCW chirps are non-uniform FMCW chirpshaving chirp profiles that differ from one another, and control logiccoupled to the radar receiver and configured to process the second radarsignal, based on the non-uniform FMCW chirps in the frame, to sense oneor more parameters of an object.

Consistent with another aspect of the invention, a program product mayinclude a non-transitory computer readable medium, and program codestored on the non-transitory computer readable medium and configuredupon execution by control logic of a radar sensor for a vehicle to causea radar transmitter of the radar sensor to transmit a first radarsignal, the first radar signal including a frame associated with aplurality of frequency modulated continuous wave (FMCW) chirps, where atleast a subset of the plurality of FMCW chirps are non-uniform FMCWchirps having chirp profiles that differ from one another, cause a radarreceiver of the radar sensor to receive a second radar signal that is areflected signal of the first radar signal, and process the second radarsignal, based on the non-uniform FMCW chirps in the frame, to sense oneor more parameters of an object in a field of view of the radartransmitter.

Consistent with another aspect of the invention, a method of operating aradar sensor for a vehicle may include transmitting a first radarsignal, the first radar signal including a frame associated with aplurality of frequency modulated continuous wave (FMCW) chirps, where atleast a subset of the plurality of FMCW chirps are non-uniform FMCWchirps having chirp profiles that differ from one another, receiving asecond radar signal that is a reflected signal of the first radarsignal, and processing the second radar signal, based on the non-uniformFMCW chirps in the frame, to sense one or more parameters of an objectin a field of view of the radar transmitter.

Consistent with another aspect of the invention, a radar sensor for avehicle may include a radar transmitter configured to transmit a firstradar signal, the radar signal including a frame associated with aplurality of frequency modulated continuous wave (FMCW) chirps, wherethe plurality of FMCW chirps includes a plurality of uniform FMCW chirpshaving a first starting frequency and a first repetition interval and aplurality of non-uniform FMCW chirps having at least one of a startingfrequency that differs from the first starting frequency and arepetition interval that differs from the first repetition interval, aradar receiver configured to receive a second radar signal that is areflected signal of the first radar signal, and control logic coupled tothe radar receiver and configured to process the second radar signal byperforming a first, range transformation with fast-time samples of thesecond radar signal to generate first, coarse resolution rangeparameters, generating uniform and non-uniform data cubes respectivelyassociated with the plurality of uniform FMCW chirps and the pluralityof non-uniform FMCW chirps using the coarse resolution range parameters,performing a second transformation with the uniform data cube togenerate second parameters, where performing the second transformationintroduces ambiguities into the uniform data cube, detecting a pluralityof candidate objects in the uniform data cube, and performing a thirdtransformation with the non-uniform data cube and for the plurality ofcandidate objects to resolve at least a subset of the introducedambiguities.

Also, in some embodiments, the second and third transformations areDoppler transformations, the second parameters are Doppler parameters,and the ambiguities are Doppler ambiguities. Further, in someembodiments, the second and third transformations are beamformingtransformations, the second parameters are angle parameters, and theambiguities are angle ambiguities. In some embodiments, the first andsecond transformations each include a Fast Fourier Transform (FFT)transformation and the third transformation includes a Discrete FourierTransform (DFT) transformation.

Some embodiments may also include enhancing range resolution for atleast a subset of the plurality of candidate objects using thenon-uniform data cube. Also, in some embodiments, the radar transmitteris a multiple input multiple output (MIMO) radar transmitter including aplurality of transmit channels and the radar receiver is a MIMO radarreceiver including a plurality of receive channels, WHERE the firstradar signal is generated for a first transmit channel of the pluralityof transmit channels and the second radar signal is received by a firstreceive channel of the plurality of receive channels, and the controllogic is further configured to perform MIMO demodulation prior togenerating the uniform and non-uniform data cubes.

Consistent with another aspect of the invention, a autonomous vehiclecontrol system may include a radar transmitter configured to transmit afirst radar signal, the first radar signal including a frame associatedwith a plurality of frequency modulated continuous wave (FMCW) chirps,where at least a subset of the plurality of FMWC chirps are non-uniformFMCW chirps having chirp profiles that differ from one another, a radarreceiver configured to receive a second radar signal that is a reflectedsignal of the first radar signal, and control logic coupled to the radarreceiver and configured to process the second radar signal, based on thenon-uniform FMCW chirps in the frame, to sense one or more parameters ofan object in a field of view of the radar transmitter.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts described in greater detail herein arecontemplated as being part of the subject matter disclosed herein. Forexample, all combinations of claimed subject matter appearing at the endof this disclosure are contemplated as being part of the subject matterdisclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example environment in which implementationsdisclosed herein can be implemented.

FIG. 2 illustrates an example implementation of a Multiple InputMultiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radarsensor that may be utilized by implementations disclosed herein.

FIG. 3 illustrates an example virtual antenna array capable of beingproduced by a MIMO FMCW radar sensor that may be utilized byimplementations disclosed herein.

FIG. 4 illustrates an example transmitter channel for the MIMO FMCWradar sensor of FIG. 2 .

FIG. 5 illustrates an example receiver channel for the MIMO FMCW radarsensor of FIG. 2 .

FIG. 6 illustrates an example process for sensing objects in anenvironment with various implementations disclosed herein.

FIG. 7 illustrates a sequence of uniform FMCW chirps.

FIG. 8 illustrates a sequence of non-uniform FMCW chirps with chirpprofiles having differing starting frequencies.

FIG. 9 illustrates a sequence of non-uniform FMCW chirps with chirpprofiles having differing starting frequencies and repetition intervals.

FIG. 10 illustrates an example process for sensing objects in anenvironment using non-uniform FMCW chirps with various implementationsdisclosed herein.

FIG. 11 illustrates an example fast time/slow time space for anidealized time domain.

FIG. 12 illustrates an example fast time/slow time space for asparsified version of the idealized time domain of FIG. 11 based uponsub-band sampling in accordance with various implementations disclosedherein.

FIG. 13 illustrates repetition interval variances in a sequence ofinterleaved uniform and non-uniform FMCW chirps.

FIG. 14 illustrates starting frequency variances in a sequence ofinterleaved uniform and non-uniform FMCW chirps.

FIG. 15 illustrates an example process for generating a frame withinterleaved uniform and non-uniform FMCW chirps with variousimplementations disclosed herein.

FIG. 16 illustrates an example process for processing a frame withinterleaved uniform and non-uniform FMCW chirps with variousimplementations disclosed herein.

DETAILED DESCRIPTION

The herein-described implementations are generally directed to variousimprovements associated with Frequency Modulated Continuous Wave (FMCW)radar sensors, e.g., for use in connection with the control of anautonomous or other type of vehicle, among other applications. Further,as will become more apparent below, the herein-described techniques mayalso be utilized in some implementations within Multiple Input MultipleOutput (MIMO) FMCW radar sensors. Prior to discussing such improvements,however, a brief discussion of an autonomous vehicle environment and ofMIMO and/or FMCW radar sensors are provided below.

Autonomous Vehicle Environment

Turning to the Drawings, wherein like numbers denote like partsthroughout the several views, FIG. 1 illustrates an autonomous vehicle100 suitable for utilizing the various techniques described herein.Vehicle 100, for example, may include a powertrain 102 including a primemover 104 powered by an energy source 106 and capable of providing powerto a drivetrain 108, as well as a control system 110 including adirection control 112, a powertrain control 114, and brake control 116.Vehicle 100 may be implemented as any number of different types ofvehicles, including vehicles capable of transporting one or both ofpeople and cargo, and it will be appreciated that the aforementionedcomponents 102-116 may vary widely based upon the type of vehicle withinwhich these components are utilized.

The implementations discussed hereinafter, for example, will focus on awheeled land vehicle such as a car, van, truck, bus, etc. In suchimplementations, the prime mover 104 may include one or more electricmotors, an internal combustion engine, or a combination thereof (amongothers). The energy source 106 may include, for example, one or more ofa fuel system (e.g., providing gasoline, diesel, hydrogen, etc.), abattery system, solar panels or other renewable energy source, and afuel cell system. Drivetrain 108 may include one or more of wheels,tires, a transmission and any other mechanical drive components suitablefor converting the output of prime mover 104 into vehicular motion, aswell as one or more brakes configured to controllably stop or slow thevehicle 100 and direction or steering components suitable forcontrolling the trajectory of the vehicle 100 (e.g., a rack and pinionsteering linkage enabling one or more wheels of vehicle 100 to pivotabout a generally vertical axis to vary an angle of the rotationalplanes of the wheels relative to the longitudinal axis of the vehicle).In some implementations, combinations of powertrains and energy sourcesmay be used (e.g., in the case of electric/gas hybrid vehicles), and insome instances multiple electric motors (e.g., dedicated to individualwheels or axles) may be used as a prime mover.

Direction control 112 may include one or more actuators, one or moresensors, or a combination thereof for controlling and receiving feedbackfrom the direction or steering components to enable the vehicle 100 tofollow a desired trajectory. Powertrain control 114 may be configured tocontrol the output of powertrain 102, e.g., to control the output powerof prime mover 104, to control a gear of a transmission in drivetrain108, etc., thereby controlling one or more of a speed and direction ofthe vehicle 100. Brake control 116 may be configured to control one ormore brakes that slow or stop vehicle 100, e.g., disk or drum brakescoupled to the wheels of the vehicle.

Other vehicle types will necessarily utilize different powertrains,drivetrains, energy sources, direction controls, powertrain controls andbrake controls, as will be appreciated by those of ordinary skill havingthe benefit of the instant disclosure. Moreover, in some implementationssome of the components may be combined, e.g., where directional controlof a vehicle is primarily handled by varying an output of one or moreprime movers. Therefore, implementations disclosed herein not limited tothe particular application of the herein-described techniques in anautonomous wheeled land vehicle.

In the illustrated implementation, full or semi-autonomous control overvehicle 100 is implemented in a vehicle control system 120, which mayinclude one or more processors 122 and one or more memories 124, witheach processor 122 configured to execute program code instructions 126stored in a memory 124. The processor(s) 122 may include, for example,one or more graphics processing units (GPUs), one or more centralprocessing units (CPUs), or a combination thereof.

Sensors 130 may include various sensors suitable for collectinginformation from a vehicle's surrounding environment for use incontrolling the operation of the vehicle. For example, sensors 130 mayinclude one or more Radio Detection and Ranging (RADAR) sensors, withwhich a number of the techniques described herein may be implemented.

Sensors 130 may also optionally include one or more Light Detection andRanging (LIDAR) sensors 132, as well as one or more satellite navigation(SATNAV) sensors 138, e.g., compatible with any of various satellitenavigation systems such as GPS, GLONASS, Galileo, Compass, etc. EachSATNAV sensor 138 may be used to determine the location of the vehicleon the Earth using satellite signals. Sensors 130 may also optionallyinclude one or more cameras 140, one or more inertial measurement units(IMUS) 142, one or more wheel encoders 144, or a combination thereof.Each camera 140 may be a monographic or stereographic camera and mayrecord one or more of still and video imagers. Each IMU 142 may includemultiple gyroscopes and accelerometers capable of detecting linear androtational motion of the vehicle 100 in three directions. Wheel encoders144 may be used to monitor the rotation of one or more wheels of vehicle100.

The outputs of sensors 130 may be provided to a set of controlsubsystems 150, including, for example, a localization subsystem 152, aperception subsystem 154, a planning subsystem 156, and a controlsubsystem 158. As will become more apparent hereinafter, radar sensors132 may be used by one or more of such subsystems 152-158 to control anautonomous vehicle.

Localization subsystem 152 may be principally responsible for preciselydetermining the location and orientation (also sometimes referred to as“pose”) of vehicle 100 within its surrounding environment, and generallywithin some frame of reference.

Perception subsystem 154 may be principally responsible for detecting,tracking and identifying elements within the environment surroundingvehicle 100. For example, perception subsystem 154 may, at each of aplurality of iterations, determine a pose, classification, and velocityfor each of one or more objects in the environment surrounding vehicle100. Further, for example, the perception subsystem 154 may trackvarious objects over multiple iterations. For instance, the perceptionsubsystem 154 may track an additional vehicle over multiple iterationsas the additional vehicle moves relative to vehicle 100.

Planning subsystem 156 may be principally responsible for planning atrajectory for vehicle 100 over some timeframe given a desireddestination as well as the static and moving objects within theenvironment. For example, and as described herein, planning subsystem156 may plan a trajectory for vehicle 100 based at least in part on oneor more of a pose, classification, and velocity for each of one or moreobjects in an environment of the vehicle 100 in the environmentsurrounding vehicle 100. In some implementations, planning subsystem 156may plan the trajectory for the vehicle 100 by generating, andconsidering, candidate trajectories for each of one or more additionalmobile objects in the environment. Planning subsystem 156 may determinea candidate trajectory for an object at an iteration based on a pose,classification, velocity, or a combination thereof for the iteration,and may track the object over multiple iterations.

Control subsystem 158 may be principally responsible for generatingsuitable control signals for controlling the various controls in controlsystem 110 in order to implement the planned trajectory of the vehicle100.

It will be appreciated that the collection of components illustrated inFIG. 1 for vehicle control system 120 is merely exemplary in nature.Individual sensors may be omitted in some implementations. Additionallyor alternatively, in some implementations multiple sensors of the typesillustrated in FIG. 1 may be used for redundancy or to cover differentregions around a vehicle, and other types of sensors may be used.Likewise, different types and combinations of control subsystems may beused in other implementations. Further, while subsystems 152-158 areillustrated as being separate from processors 122 and memory 124, itwill be appreciated that in some implementations, some or all of thefunctionality of a subsystem 152-158 may be implemented with programcode instructions 126 resident in one or more memories 124 and executedby one or more processors 122, and that these subsystems 152-158 may insome instances be implemented using the same processors and memory.Subsystems in some implementations may be implemented at least in partusing various dedicated circuit logic, various processors, variousfield-programmable gate arrays (“FPGA”), various application-specificintegrated circuits (“ASIC”), various real time controllers, and thelike, and as noted above, multiple subsystems may utilize circuitry,processors, sensors or other components. Further, the various componentsin vehicle control system 120 may be networked in various manners.

In some implementations, vehicle 100 may also include a secondaryvehicle control system (not illustrated), which may be used as aredundant or backup control system for vehicle 100. In someimplementations, the secondary vehicle control system may be capable offully operating autonomous vehicle 100 in the event of an adverse eventin vehicle control system 120, while in other implementations, thesecondary vehicle control system may only have limited functionality,e.g., to perform a controlled stop of vehicle 100 in response to anadverse event detected in primary vehicle control system 120. In stillother implementations, the secondary vehicle control system may beomitted.

In addition, while powertrain 102, control system 110, and vehiclecontrol system 120 are illustrated in FIG. 1 as being separate systems,in other implementations, some of all of these systems may be combinedinto a single system, e.g., with control system 110 and vehicle controlsystem 120 combined into a single autonomous vehicle control system, orusing other combinations. Further, in other implementations, some or allof the functionality illustrated as being within one system in FIG. 1may be implemented in another system.

In general, an innumerable number of different architectures, includingvarious combinations of software, hardware, circuit logic, sensors,networks, etc. may be used to implement the various componentsillustrated in FIG. 1 . Each processor may be implemented, for example,as a microprocessor and each memory may represent the random accessmemory (RAM) devices comprising a main storage, as well as anysupplemental levels of memory, e.g., cache memories, non-volatile orbackup memories (e.g., programmable or flash memories), read-onlymemories, etc. In addition, each memory may be considered to includememory storage physically located elsewhere in vehicle 100, e.g., anycache memory in a processor, as well as any storage capacity used as avirtual memory, e.g., as stored on a mass storage device or on anothercomputer or controller. One or more processors illustrated in FIG. 1 ,or entirely separate processors, may be used to implement additionalfunctionality in vehicle 100 outside of the purposes of autonomouscontrol, e.g., to control entertainment systems, to operate doors,lights, convenience features, etc. Processors may also be implemented inwhole or in part within individual sensors in some implementations.

In addition, for additional storage, vehicle 100 may also include one ormore mass storage devices, e.g., one or more of a removable disk drive,a hard disk drive, a direct access storage device (DASD), an opticaldrive (e.g., a CD drive, a DVD drive, etc.), a solid state storage drive(SSD), network attached storage, a storage area network, and a tapedrive, among others. Furthermore, vehicle 100 may include a userinterface 164 to enable vehicle 100 to receive a number of inputs fromand generate outputs for a user or operator, e.g., one or more displays,touchscreens, voice interfaces, gesture interfaces, buttons and othertactile controls, etc. Otherwise, user input may be received via anothercomputer or electronic device, e.g., via an app on a mobile device orvia a web interface.

Moreover, vehicle 100 may include one or more network interfaces, e.g.,network interface 162, suitable for communicating with one or morenetworks (e.g., one or more of a LAN, a WAN, a wireless network, and theInternet, among others) to permit the communication of information withother computers and electronic devices, including, for example, acentral service, such as a cloud service, from which vehicle 100receives environmental and other data for use in autonomous controlthereof.

Each processor illustrated in FIG. 1 , as well as various additionalcontrollers and subsystems disclosed herein, generally operates underthe control of an operating system and executes or otherwise relies uponvarious computer software applications, components, programs, objects,modules, data structures, etc., as will be described in greater detailbelow. Moreover, various applications, components, programs, objects,modules, etc. may also execute on one or more processors in anothercomputer coupled to vehicle 100 via network, e.g., in a distributed,cloud-based, or client-server computing environment, whereby theprocessing required to implement the functions of a computer program maybe allocated to multiple computers or services over a network.

In general, the routines executed to implement the variousimplementations described herein, whether implemented as part of anoperating system or a specific application, component, program, object,module or sequence of instructions, or even a subset thereof, will bereferred to herein as “program code.” Program code typically comprisesone or more instructions that are resident at various times in variousmemory and storage devices, and that, when read and executed by one ormore processors, perform the steps necessary to execute steps orelements embodying the various aspects of the invention. Moreover, whileimplementations have and hereinafter will be described in the context offully functioning computers and systems, it will be appreciated that thevarious implementations described herein are capable of beingdistributed as a program product in a variety of forms, and thatimplementations may be implemented regardless of the particular type ofcomputer readable media used to actually carry out the distribution.Examples of computer readable media include tangible, non-transitorymedia such as volatile and non-volatile memory devices, floppy and otherremovable disks, solid state drives, hard disk drives, magnetic tape,and optical disks (e.g., CD-ROMs, DVDs, etc.), among others.

In addition, various program code described hereinafter may beidentified based upon the application within which it is implemented ina specific implementation. However, it should be appreciated that anyparticular program nomenclature that follows is used merely forconvenience, and thus the invention should not be limited to use solelyin any specific application identified or implied by such nomenclature.Furthermore, given the typically endless number of manners in whichcomputer programs may be organized into routines, procedures, methods,modules, objects, and the like, as well as the various manners in whichprogram functionality may be allocated among various software layersthat are resident within a typical computer (e.g., operating systems,libraries, API's, applications, applets, etc.), it should be appreciatedthat the invention is not limited to the specific organization andallocation of program functionality described herein.

MIMO FMCW Radar Sensors

FIG. 2 next illustrates an example radar sensor 200 within which thevarious techniques described herein may be implemented. In someimplementations, radar sensor 200 may be a distributed radar sensor. Insome implementations, sensor 200 includes one or more MIMO radartransceivers (e.g., transceivers 202A and 202B) coupled to a controller204, with each MIMO radar transceiver generally including multipletransmit (Tx) antennas (e.g., transmit antennas 206A, 206B) and multiplereceive (Rx) antennas (e.g., receive antennas 208A, 208B) to implement aphased antenna array.

Each transceiver 202A, 202B may be disposed on a separate integratedcircuit (IC) or chip in some implementations, while in otherimplementations multiple transceivers may be disposed on the same chip.Further, multiple transceivers 202A, 202B may be disposed on separate orcommon modules, boards, cards, or housings in various implementations.In addition, it will be appreciated that, rather than utilizingtransceivers that handle both transmission and reception of radarsignals, some implementations may utilize separate circuitry for thesefunctions.

Controller 204 is generally coupled to one or more transceivers. Forexample, controller 204 is coupled to each transceiver 202A, 202B forcontrolling both (i) the generation of radar signals for transmission oremission by transmit antennas 206A, 206B and (ii) the reception andprocessing of radar signals received by receive antennas 208A, 208B. Itwill be appreciated that the functionality implemented by controller 204may be allocated in various manners in different implementations, e.g.,using one or more chips that are separate from each transceiver 202A,202B and disposed on the same or different module, board, card orhousing, or being wholly or partially integrated into the same chips asone or more of the transceivers. The functionality of controller 204 mayalso be at least partially implemented external of any radar sensor insome implementations, e.g., integrated into other processors orcontrollers in the vehicle control system of an autonomous vehicle.Further, while a single controller 204 is illustrated in FIG. 2 , theinvention is not so limited, as multiple controllers may be used toimplement different functionality in a radar sensor in someimplementations, e.g., using multiple controllers integrated with eachtransceiver 202A, 202B. In some implementations, one or more ofcontroller 204 and transceivers 202A, 202B may be implemented using oneor more Monolithic Microwave Integrated Circuits (MMICs).

As such, it will be appreciated that the functionality described hereinmay in some implementations be implemented using various types ofcontrol logic, whether integrated into a transmitter, receiver ortransceiver, processor, controller, computer system, etc., whetherdisposed on one or more integrated circuit chips, and whetherincorporating hardwired logic or programmable logic capable of executingprogram code instructions. Control logic may also be considered toinclude analog circuitry, digital circuitry, or both in variousimplementations. As such, the invention is not limited to the particularcontrol logic implementation details described herein.

Likewise, transmit antennas 206A, 206B and receive antennas 208A, 208Bmay be implemented in a wide variety of manners, e.g., as patch antennasdisposed on one or more printed circuit boards or cards, or in someinstances disposed on or in a package or chip and thus integrated with atransceiver or controller of the radar sensor, e.g., using antenna onpackaging (AOP) or antenna on chip (AOC) technology. Antennas 206A,206B, 208A, 208B may be omnidirectional or directional in differentimplementations. In some implementations, the same antennas may be usedfor both transmit and receive; however, in the illustratedimplementations, separate antennas are used to handle the transmissionand reception of radar signals. Therefore, a reference to an antenna asbeing a transmit antenna or a receive antenna herein does notnecessarily require that the antenna be used exclusively for thatpurpose.

Antennas 206A, 206B, 208A, 208B in the illustrated implementations aredesirably physical arranged and electronically controlled to implement aMIMO virtual antenna array (VAA), i.e., an array of virtual arrayelements that individually represent unique transmit/receive antennapairs. FIG. 3 , for example, illustrates an example virtual antennaarray 220 formed from a set of three physical transmit antennas 222(Tx1, Tx2, Tx3, each of which corresponding, for example, to a transmitantenna 206A, 206B in FIG. 2 ) and four physical receive antennas 224(Rx1, Rx2, Rx3, Rx4, each of which corresponding, for example, to areceive antenna 208A, 208B in FIG. 2 ), which together form a virtualantenna array having a 3×4 or 12 element array of virtual array elements226, thereby increasing the effective number of antennas and improvingcross-range resolution. It will be appreciated that different numbers orarrangements of physical transmit and receive antennas may be used toform different sizes and arrangements of virtual antenna arrays, so theinvention is not limited to the specific array illustrated in FIG. 3 .

Increasing the numbers of physical transmit antennas and physicalreceive antennas for a virtual antenna array, and thus the number ofvirtual array elements in the virtual antenna array, may generally beused to increase angular resolution, detection range or signal to noiseratio. In one example implementation, an individual transceiver chiphaving three transmit antennas and four receive antennas may be used toform a virtual antenna array having twelve virtual array elements, whichmay, in some instances, be used to form a one dimensional array of <5 cmlength (e.g., emphasizing azimuth resolution) or in other instances forma two dimensional of at most about 1 cm×1 cm (e.g., providing coarseresolution in both azimuth and elevation). If four of such transceiverchips are used in the same virtual antenna array, however, a total of 12transmit antennas and 16 receive antennas may be used to generate 192virtual array elements. Such element counts may be used for example, togenerate two dimensional array layouts over about a 10 cm×10 cm area,and allowing for an angular resolution of a few degrees in both azimuthand elevation.

Now turning to FIGS. 4 and 5 , these figures respectively illustrateexample transmit and receive channels or paths for individual transmitand receive antennas 206A, 206B, 208A, 208B in transceiver 202A (itbeing understood that similar components may be used for othertransceivers such as transceiver 202B). Each transmit and receivechannel or path utilizes millimeter wave frequency modulated continuouswave (FMCW) radar signals in this implementation, and while radar sensor200 utilizes multiple such channels or path in a MIMO arrangement, itwill be appreciated that the principles of the invention may also beutilized in non-MIMO FMCW radar sensors as well, such that an FMCW radarsensor in some implementations may include as few as one transmit orreceive channel or path.

In the transmit channel of transceiver 202A as illustrated in FIG. 4 , alocal oscillator (LO) 230 generates an FMCW radio frequency (RF) signal,e.g., in the range of 76 GHz to 81 GHz. The FMCW RF signal is amplifiedby an amplifier 232 to drive a transmit antenna 206A. The frequency ofLO 230 is determined by a modulator block 234, which is capable offrequency modulating LO 230 to effectively generate pulsed signals orsweep signals referred to as chirps, e.g., using sawtooth or anotherform of frequency modulation. Control over modulator block 234 may beprovided by a controller 236, which in some instances may be controller204, while in other instances may be other control logic, e.g., as maybe integrated into transceiver 202A. Controller 236 may be used tocontrol various parameters of the chirps, e.g., start frequency, phase,repetition interval, slope, duration, chirp rate, etc., as well as totrigger the initiation of a chirp.

In the receive channel of transceiver 202A as illustrated in FIG. 5 , areceived RF signal from an antenna 208A is amplified by an amplifier 238and then mixed with the LO 230 signal by a mixer 240 to generate a mixedsignal. The mixed signal is filtered by a filter 242 and digitized by ananalog to digital converter (ADC) 244 to generate a stream of digitalsignals. For example, the digital signals can be data samples, which inthe illustrated implementation may be considered to be digital valuesoutput by ADC 244, and which may in some implementations include otheridentifying data such as the channel, transmit antenna, receive antenna,chirp number, timestamp, etc. associated with the digital value. Thedigital signals are provided to controller 236.

It will be appreciated that in different implementations, variouscomponents among components 230-244 of FIGS. 4 and 5 may be shared bymultiple transmit channels or multiple receive channels and thatmultiple instances of some components may be dedicated to differentchannels. Further, other architectures may be used to implement transmitchannels or receive channels in other implementations, so the inventionis not limited to the specific architecture illustrated in FIGS. 4-5 .In addition, in some implementations, controller 236 may be replaced bycontroller 204 of radar sensor 200. In these implementations, controller204 of radar sensor 200 may control one or more components of components230-244 described with reference to FIGS. 4 and 5 .

FIG. 6 next illustrates diagrams showing general operations of a radarsensor and data generated by the radar sensor. For example, the radarsensor may be an FMCW MIMO radar sensor such as radar sensor 200discussed above in connection with FIGS. 2-5 . Graph 252, for example,illustrates a simplified time vs. frequency graph of a sequence ofchirps. A chirp may represent a sweeping signal across frequency in acertain cycle. For example, a chirp CH1 is a sweeping signal duringcycle C1, a chirp CH2 is a sweeping signal during cycle C2, and a chirpCH3 is a sweeping signal during cycle C3. In this example, chirpsCH1-CH3 are illustrated as repetitions of sweeping signals having thesame shape. However, in some implementations, chirps may dwindle overtime. In addition, in this example graph, chirps C1-C3 are linearlymodulated to have a sawtooth shape. However, in some implementations,the chirps may be modulated non-linearly or may be modulated to have anyshape. Graph 252 shows both a transmitted signal 254 (which matches thefrequency of the local oscillator) for a transmit channel Tx andreceived signals 256, 258 for two objects located at different rangesand received by a receive channel Rx. In this example, the transmittedsignal 254 represents a sequence of chirps. As shown in this graph, thetime delay from transmission of the transmit signal to being receivedfor the two objects causes a difference in frequency, e.g., illustratedby D1 for a first object and D2 for a second object.

In some implementations, data samples collected by radar sensor 200 maybe processed to generate radar data associated with certain features.For example, the radar data may be represented as data cubes associatedwith certain features. The features may be represented as dimensions ofthe data cubes where the features include, but are not limited to, fasttime (the number of samples in one chirp), slow time (the number ofchirps in one set of chirps, also referred to as a frame), and thenumber of receive channels. Where a local oscillator is operated atabout 77 GHz, a controller (e.g., controller 204 in FIG. 2 or controller236 in FIGS. 4 and 5 ) may process received data samples such that eachframe may include 128-512 chirps and 512-1024 samples per chirp. In thisexample, a frame firing duration (also referred to as a coherentprocessing interval (CPI) may be about 5-15 ms/frame, a sample rate maybe about 20 million samples/second, and a chirp duration may be about25-100 microseconds per chirp. In some implementations, receive channels(e.g., about 4-16 Rx channels) may be processed in parallel. Althoughspecific numbers are provided in this paragraph, they are provided asexamples and any suitable numbers can be used to implement radarsensors.

Radar data (e.g., data cubes) may be processed to determine, for one ormore objects (also sometimes referred to as targets) in the field ofview of a radar sensor, (i) range from the radar sensor to a respectiveobject, (ii) Doppler velocity (i.e., radial velocity of the respectiveobject relative to the radar sensor), or (iii) angle of arrival, interms of one or both of azimuth and elevation. First, as illustrated at260, sampling may be performed on each receive channel over multiplechirps in a frame or CPI. The samples for all of the chirps in the framefor a particular Tx/Rx pair may be incorporated into a two dimensionalarray 262 where the samples are arranged in one dimension by samplenumber (vertical axis of FIG. 6 , from first sample to last samplecollected for each chirp) and in another dimension by chirp number(horizontal axis of FIG. 6 , from first chirp to last chirp in a frame).In one example implementation, for example, where a frame includes 128chirps with 1024 samples in each chirp, the array may have dimensions of128 (horizontal)×1024 (vertical).

Next, range measurements are determined for the samples in each channel,generally by performing a Fast Fourier Transform (FFT) operation 264(referred to herein as a range FFT), or other frequency transformation,which recovers the frequency spectrum from the digital samples in eachchannel to generate a range profile (power vs. range) in the frequencydomain for each chirp for a particular Tx/Rx pair. It will beappreciated, in particular, that an object at a given range from a radarsensor will delay the transmitted signal 254 by a delay that isproportional to its range, and that this delay remains substantiallyconstant over a chirp. Given that the mixed signal output by mixer 240of FIG. 5 is effectively the difference in the instantaneous frequenciesof the transmitted and received signals within a given channel, and thatthis difference is substantially constant over a chirp, the reflectioncorresponding to the object effectively generates a constant frequency“tone” in the mixed signal that resolves to a peak in the frequencydomain at that frequency. Multiple objects therefore resolve to a rangeprofile having different peaks in the frequency domain corresponding tothe ranges of those objects, and may be grouped in some implementationsinto frequency bins corresponding to different ranges in the field ofview of the radar sensor.

Each range profile for a particular chirp may be considered to be a onedimensional array representing power over a range of frequencies forthat chirp. The range profiles for the chirps in the frame may thereforealso be stacked into an array 266 having one dimension representingranging frequency or frequency bin (vertical axis in FIG. 6 ) and onedimension representing chirp number (horizontal axis in FIG. 6 ), and itmay be seen by the representation of array 266 that horizontal linesgenerally represent frequency bins where potential objects at variousranges corresponding to those frequency bins have been detected over thecourse of multiple chirps in a frame.

Next, velocity measurements (e.g., Doppler measurements) are determinedfor the samples in each channel, generally by performing a second FFToperation 268 (referred to herein as a Doppler FFT) to recover phaseinformation corresponding to Doppler shifts. Transforming across the setof chirps results in a data set that may be represented by an array 270arranged by ranging frequency or frequency bin (vertical axis) andDoppler frequency or frequency bin (horizontal axis), where each Dopplerfrequency bin generally corresponds to a particular velocity for apotential object disposed within a particular range frequency bin.

Next, beamforming is performed to determine angle of arrivalinformation. It should be noted that arrays 262, 266 and 270 are eachbased on the samples for a single transmit channel/receive channel(Tx/Rx) pair. Thus, a stacking operation 272 may be performed to stackthe arrays 270 generated by the Doppler FFT operation for differentTx/Rx pairs (also referred to as array elements) into a data stack 274.

It will be appreciated that each different Tx/Rx pair may have adifferent spatial relationship between the respective physical transmitand receive antennas for the pair, which can lead to slightly differentphases reported for the same object for different Tx/Rx pairs. In thecase of a uniform linear array, a third FFT operation 276 (referred toherein as a beamforming FFT) may therefore use the set of values acrossthe different array elements in stack 274 (also referred as abeamvector) to estimate an angle of arrival at each range-Dopplerlocation (i.e., each combination of range frequency bin and Dopplerfrequency bin). More generally, a set of complex responses expected forsome set of azimuth and elevation angles of arrival, also known assteering vectors, may be multiplied onto the beamvectors to generateazimuth and elevation angles for each object (represented by graphs278).

Then, the aforementioned range, Doppler and angle of arrival informationmay be combined in some implementations by a point cloud generationoperation 280 into a three dimensional point cloud 282 includingestimated position (e.g., using cartesian or polar coordinates),velocity, and signal intensity (or confidence) for a plurality ofobjects in the field of view of the radar sensor.

It will be appreciated that a wide variety of modifications andenhancements may be made to the aforementioned operations of FIG. 6 , sothe invention is not limited to this specific sequence of operations.

Those skilled in the art, having the benefit of the present disclosure,will recognize that the exemplary environment illustrated in FIGS. 1-6is not intended to limit implementations disclosed herein. Indeed, thoseskilled in the art will recognize that other alternative hardware orsoftware environments may be used without departing from the scope ofimplementations disclosed herein. It will also be appreciated that thevarious FMCW radar techniques described herein may be utilized inconnection with other applications, so the invention is not limited toFMCW radars or radar sensing systems used solely in connection with thecontrol of an autonomous vehicle.

Subsampling with Non-Uniform FMCW Chirps for EnhancedRange/Doppler/Angle Performance

The ADC sampling rate on FMCW radar chipsets generally imposes a stricttradeoff between range and Doppler performance. For a desiredoperational range, this limit forces a tradeoff between range resolutionand Doppler ambiguity as mediated by the required duration of a chirp.Range resolution, for example is generally related to bandwidth asc/(2*bandwidth) (where c is the speed of light), while maximum ambiguousvelocity is generally calculated as wavelength/(4*chirp_period). Often,this tradeoff leads to a maximum Doppler that is less than the maximumexpected value in real-world scenarios. One solution to this problem isto modulate the maximum unambiguous Doppler frame-to-frame so thatambiguities may be resolved; however, the range resolution at thisset-point is also generally less than desired. Some conventional FMCWradar designs, for example, include a 350 m range mode, with a 70 cmrange resolution and about a +/−20 m/s (about +/−45 MPH) Dopplerambiguity. An “ideal” radar, however, would maintain this maximum rangewhile reducing both the range bin size and extending the maximum Dopplerto better account for real world automotive environments.

The implementations discussed herein, on the other hand, may utilize theconcept of non-uniform FMCW chirps within a frame of an FMCW radarsignal, coupled with appropriate processing thereof of a received radarsignal, to better address these tradeoffs and thereby enhance radarperformance with respect to parameters such as range, Doppler or angleof various objects in the field of view of a radar signal. Specifically,a vehicle radar sensor in some implementations may include a radartransmitter configured to transmit a first radar signal that includes aframe associated with a plurality of FMCW chirps, with at least a subsetof the FMCW chirps being non-uniform FMCW chirps and having chirpprofiles that differ from one another. The vehicle radar sensor may alsoinclude a radar receiver configured to receive a second radar signalthat is a reflected signal of the first radar signal, and control logicthat is coupled to the radar receiver and configured to decode thesecond radar signal, and to use the non-uniform FMCW chirps in the frameto sense one or more parameters of one or more objects in a field ofview of the radar transmitter.

FMCW chirps are non-uniform within the context of this disclosure basedupon the FMCW chirps within the same frame having differing chirpprofiles, and in some implementations, having chip profiles that differfrom some default or baseline chirp profile that may be used in a frame,e.g., for uniform FMCW chirps in a frame that share the same chirpprofile. A chirp profile, in this regard, refers to various transmissionparameters or characteristics of a chirp, including, for example, one ormore of a starting frequency, a duration, a slope, and a repetitioninterval. In the implementations discussed hereinafter, for example,non-uniform FMCW chirps within a frame may vary from one another interms of one or both of starting frequency and repetition interval,while sharing the same duration and slope, and in some implementations,these non-uniform FMCW chirps may be accompanied within a frame withuniform FMCW chirps that have the same starting frequency, repetitioninterval, duration and slope. It will be appreciated, however, thatnon-uniform FMCW chirps and chirp profiles may vary from one anotherbased upon other transmission parameters and/or combinations oftransmission parameters in other implementations, so the invention isnot limited to the specific chirp profile variations discussed herein.

The manner in which the chirp profiles of non-uniform FMCW chirps may bevaried in different implementations. It will be appreciated, forexample, that some commercially-available FMCW radar chipsets provide anoption to alter chirp profile parameters such as starting frequency andrepetition interval on an individual (chirp-by-chirp) basis. Othermanners of controlling the chirp profiles of FMCW chirps emitted by aradar transmitter, however, will be appreciated by those of ordinaryskill in the art having the benefit of the instant disclosure.

In the herein-described implementations, non-uniform FMCW chirps areutilized to leverage faster, lower bandwidth chirps with a pattern offrequency and duration randomization across a frame of chirps. Thefrequency randomization may be used to extend the bandwidth coveredwithin a frame for higher range resolution, and the frequencyrandomization and duration randomization may be used to substantiallyincrease the maximum detectable velocity. It will be appreciated thatsuch “randomization” may also include pseudo-random sequences inaddition to purely random sequences, as well as predetermined sequences(e.g., based on empirical analysis) that sufficiently distributefrequency and/or duration variations within a frame over both theoverall frequency bandwidth and duration of the frame.

In some aspects, the non-uniform FMCW chirps may be configured toeffectively enable subsampling to be performed on one or more dimensionsto enhance the resolution of parameters such as range, Doppler and/orangle. For example, subsampling on the range dimension may be enabledthrough carrier frequency shredding, whereby the total band is splitinto multiple subbands carried by different non-uniform FMCW chirpshaving differing starting frequencies. Likewise, subsampling on theDoppler dimension may be used to disambiguate Doppler ambiguityintroduced as a result of low computational overhead Dopplertransformations such as Doppler FFT operations, and subsampling onelevation and/or azimuth angles may be used to disambiguate angle oraperture ambiguity introduced as a result of low computational overheadbeamforming transformations such as beamforming FFT operations.

FIGS. 7-9 illustrate example uniform (FIG. 7 ) and non-uniform (FIGS. 8and 9 ) FMCW chirps that may be used in some implementations. FIG. 7 ,in particular, illustrates at 290 a sequence of uniform FMCW chirpshaving substantially the same starting frequency, duration, slope andrepetition interval, and it will be appreciated that with such uniformFMCW chirps, range resolution is determined by chirp bandwidth (hereabout 250 MHz) and ghost velocities will be introduced, resulting inDoppler ambiguity. FIG. 8 illustrates at 292 a sequence of non-uniformFMCW chirps that vary from one another based on starting frequency, withthe other aspects of the chirp profile, duration, slope and repetitioninterval, substantially the same among all of the chirps. It will beappreciated that a larger total bandwidth is occupied by all the chirpscompared to FIG. 7 (about 700 MHz illustrated, vs. about 250 MHz foreach chirp), leading to enhanced range resolution. Further, greaterrejection of ghost velocities occurs compared to true object velocity.FIG. 9 illustrates at 294 a sequence of non-uniform FMCW chirps thatvary from one another based on both starting frequency and repetitioninterval, with the other aspects of the chirp profile, duration andslope, substantially the same among all of the chirps. Enhanced Dopplersidelobe rejection occurs compared to FIG. 8 due to greaterrandomization from repetition interval variations.

Resolving range and Doppler from non-uniform FMCW chirps may occur asdescribed below. Assume, for example, a transmitted (Tx) FMCW radarsignal such as:

x _(tx)(t)=A*exp(j*2π(f _(c,n) t _(s)+0.5*αt _(s) ²)+φ₀)  (1)

Also assume a single object in the scene for explanation, and that theobject is assumed to be located at distance of R and moving at arelative speed of V. φ₀ is the initial phase of each chirp, therepetition interval of chirp n is T_(n), the sampling interval in onechirp is t_(s), the center carrier frequency of chirp n is f_(c,n) andthe chirp slope is α. The transmission delay at chirp n is:

τn=2(R _(n) +Vt _(s))/c=2(R+V*(ΣT _(n))+Vt _(s)))/c  (2)

The received (Rx) FMCW radar signal will be:

x _(rx)(t)=B*exp(j*2π(f _(c,n)(t _(s)−τ)+0.5*α(t _(s)−τ)²+φ₀)  (3)

The beat signal after mixing x_(tx)(t) and x_(rx)(t), x_(m)(t), willthen be:

$\begin{matrix}{{x_{m}(t)} = {{x_{tx}(t)} \star {x_{rx}(t)}}} & (4)\end{matrix}$ $\begin{matrix}\left. {= {{{AB}/2} \star {\exp\left\{ {j \star {2{\pi\left( {{f_{c,n}t_{s}} + {0.5 \star {\alpha t_{s}^{2}}} - {f_{c,n}\left( {t_{s} - \tau} \right)} - {0.5 \star {\alpha\left( {t_{s} - \tau} \right)}^{2}}} \right)}}} \right.}}} \right) & (5)\end{matrix}$ $\begin{matrix}\left. {= {{{AB}/2} \star {\exp\left\{ {j \star {2{\pi\left( {{f_{c,n}\tau} + {\alpha\tau t_{s}} - {0.5 \star \alpha \star \tau^{2}}} \right)}}} \right.}}} \right) & (6)\end{matrix}$ $\begin{matrix}{= {{{AB}/2} \star {\exp\left( {j \star {2{\pi\left( {{\left( {{2\alpha R/c} + {2f_{c,n}v/c} + \text{ }{2\alpha{V\left( {\Sigma T_{n}} \right)}/c}} \right)t_{s}} + {{2f_{c,n}V} \star {\left( {\Sigma T_{n}} \right)/c}} + {2f_{c,n}R/c} + {2\alpha Vt_{s}^{2}/c}} \right)}}} \right)}}} & (7)\end{matrix}$

By ignoring unnecessary/negligible terms in Eq. (7), x_(m)(t) may berewritten as:

x _(m)(t)=AB/2*exp(j*2π((2αR/c)t _(s)+2f _(c,n) V*(ΣT _(n))/c+2f _(c,n)R/c))  (8)

Three factors may be derived from Eq. (8). The first, (2αR/c)t_(s),represents a coarse estimation of the object range provided by sub-bandbandwidth. The second, 2f_(c,n)R/c, represents phase variation along theslow time due to carrier frequency variation, which provides a finerrange resolution observation proportional to the total band frequencybandwidth coverage. The third, 2f_(c,n)V*(ΣT_(n))/c, represents thephase variation along the slow time due to both the carrier frequencyand pulse duration variation, which provides an unlimited maximumvelocity detection.

To resolve the range and doppler from a received radar signal in someimplementations may be performed in a manner illustrated by sequence ofoperations 300 of FIG. 10 . First, in block 302 a first dimension orrange transformation, such as a Fast Fourier Transform (FFT) operation,may be conducted with fast time samples to generate a coarse rangeresolution data cube including coarse resolution range parameters for aplurality of objects in the field of view of the radar sensor that arebased in part on the sub-band bandwidth covered by each chirp, and thatare arranged into range bins in a fast time dimension.

Next, in block 304 the range-FFT output data cube may be upsampled alongthe fast time dimension and phase variation according to the secondfactor (2f_(c,n)R/c from Eq. (8)) along the slow time dimension may becompensated for each of the upsampled range bins to enhance rangeresolution in the upsampled data cube. Then, in block 306 a slow timeDoppler transformation, such as a Discrete Fourier Transform (DFT)operation, may be performed according to the third factor(2f_(c,n)V*(ΣT_(n))/c from Es. (8)) to obtain enhanced Dopplerparameters for the plurality of objects.

As an alternative to a post ranging FFT phase correction, one canrecognize the equivalency of the correction to a shift of the timedomain data within a broader fast time sample space, allowing for analternative processing approach. This interpretation also offersinsights into the basis for the performance improvement. FIGS. 11 and 12, for example, respectively depict a fully sampled fast time/slow timespace 310 (FIG. 11 ) and a time-domain representation 312 of a sub-bandsampling method utilized in some of the illustrated implementations(FIG. 12 ). Here it becomes clear that the ADC limitation is translatedinto a bandwidth limitation (only sampling a sub-band of the fullbandwidth across fast time for any given chirp) while the frequencyshifting capability allows the full bandwidth to be covered. Theresulting data is essentially a sparsified version of idealized timedomain—one with better range bandwidth (range resolution) and fasterchirps (Doppler ambiguity).

It will be appreciated therefore that when applying the herein-describedtechniques one may have a choice of only shredding carrier frequencywhile keeping repetition interval constant, which still providesenhanced range detection performance. It should be noted, however, thata constant repetition interval may lead to less-random phase variationof the aforementioned third factor and therefore may generate largerDoppler sidelobes and higher possibility of Doppler ambiguity, soadditional benefits may be realized through the use of this additionalchirp non-uniformity.

In addition, in order to reduce the computational load associated withperforming the more computationally-expensive DFT operations in block306 of FIG. 10 , it may also be desirable in some implementations toutilize a “two-stage disambiguation” approach, described in greaterdetail below in connection with FIGS. 13-16 , that may reducecomputational load while still maintaining the aforementioned enhancedrange-doppler benefits.

With such an approach uniform and non-uniform FMCW chirps may beinterleaved with one another along the slow time, as illustrated inFIGS. 13 and 14 . FIG. 13 , in particular, illustrates at 316 a graph ofstarting time variations (y-axis) over a sequence of chirps (x-axis),with odd chirps using a uniform/constant repetition interval, and evenchirps using variations in starting time/repetition interval of about+/−10 μs. FIG. 14 illustrates at 318 a graph of frequency variations(y-axis) over a sequence of chirps (x-axis), with odd chirps using auniform/constant starting frequency, and even chirps using variations instarting frequency of about +/−500 MHz. This frequency variation rangecan be changed depending on the design specification, with a theoreticalmaximum range up to about +/−2 GHz. In both figures, the repetitioninterval and starting frequency variations may be implemented usingrandom, pseudorandom or predetermined sequences that distribute chirpsboth over a larger frequency band than the original chirps and over theduration of the frame.

As illustrated in FIG. 15 , an example sequence of operations forgenerating a frame of FMCW chirps is illustrated at 320, and may beimplemented, for example, using control logic of a radar sensor tocontrol a radar transmitter thereof. In addition, in someimplementations, the radar sensor may be implemented as a MIMO radarsensor, e.g., MIMO radar sensor 200 of FIGS. 2-5 , whereby sequence 320represents operations that may be performed by controller 236 togenerate a single transmit (Tx) radar signal from a transceiver 202Arepresenting a single transmit channel, and it will be understood thatother transmit channels may generate other transmit radar signalsincluding uniform and/or non-uniform FMCW chirps.

Sequence 320 in the illustrated implementation interleaves uniform andnon-uniform FMCW chirps such that a frame includes an equal number ofalternating uniform and non-uniform FMCW chirps. Thus, in block 322,sequence 320 generates a uniform FMCW chirp, which modulates a localoscillator signal and thereby causes the associated radar transmitter toemit a FMCW radar signal including the uniform FMCW chirp embeddedtherein. Next, in block 324, one or more parameters for the nextnon-uniform chirp are selected in order to generate a non-uniform chirpprofile for the next non-uniform chirp, e.g., by selecting one or moreof a starting frequency, duration, slope or repetition interval for thenon-uniform chirp according to a random, pseudorandom or predeterminedsequence. Block 326 then generates the non-uniform FMCW chirp using theselected parameter(s), which modulates the local oscillator signal andthereby causes the associated radar transmitter to emit a FMCW radarsignal including the non-uniform FMCW chirp embedded therein. Block 328determines whether the frame is complete, i.e., whether the number ofFMCW chirps equals the total number of FMCW chirps per frame, and ifnot, returns control to block 322 to generate another uniform FMCWchirp. Once all FMCW chirps have been generated for the frame, however,sequence 320 is complete. It will be appreciated that in otherimplementations, the number and/or order of uniform and non-uniform FMCWchirps may vary, so the invention is not limited to the 1:1 ratio ofuniform and non-uniform FMCW chirps illustrated in FIG. 15 .

Now turning to FIG. 16 , this figure illustrates an example sequence ofoperations 340 for processing a frame of FMCW chirps consistent withsome implementations. Sequence 340 may be implemented, for example,using control logic of a radar sensor that processes digital datasamples received from a radar receiver thereof. In addition, in someimplementations, the radar sensor may be implemented as a MIMO radarsensor, e.g., MIMO radar sensor 200 of FIGS. 2-5 , whereby sequence 340represents operations that may be performed by controller 236 to processa set of receive (Rx) radar signals from a plurality of transceivers202A representing a plurality of receive channels.

As noted above, sequence 340 employs a two-stage disambiguation approachthat uses the uniform FMCW chirps in a frame to initially, and withrelatively low computational overhead, identify potential or candidateobjects and calculate range and/or Doppler parameters therefor,generally using light-weight FFT computations when performing the rangeand/or doppler transformations. In particular, a first-stage operationin some implementations may be used to calculate range parameters withrelatively coarse range resolutions and Doppler parameters in thepresence of Doppler ambiguities. Then a first-stage detection may beapplied to select range (with coarse range resolution) and Doppler (withmultiple ambiguities) candidate objects.

Thereafter, in a second stage, the non-uniform FMCW chirps may be usedfor more computationally-expensive operations, e.g., DFT computations,that are focused on the identified candidate objects, thereby reducingthe overall computational overhead that would otherwise be required. Inparticular, second-stage slow time DFT operations correspondinggenerally to block 306 of FIG. 10 and described above may be used tocheck the finer range resolution and true/disambiguated Doppler based onthe first-stage detected candidates.

In addition, in some MIMO-based implementations, this two-stagedisambiguation approach may be further extended to one or both ofazimuth and elevation angle domains. In the angle context, the antennaarray may be conceptually separated into a uniform rectangular array anda sparse array. The uniform rectangular array features a uniform andlarge antenna gap, and may be used to initially and with relatively lowcomputational overhead calculate azimuth and/or elevation angles withlight-weight FFT operations, which provides a relatively high angleresolution but with a relatively small unambiguous field of view due tothe relatively large antenna gap. Then, in a second stage, the detectedazimuth and/or elevation values from the first-stage calculations may bedisambiguated by the sparse antenna array with morecomputational-intensive DFT operations.

Sequence 340 of FIG. 16 is an example implementation of a signalprocessing flow to combine these aforementioned 4-dimensional objectfeatures or parameters (range, Doppler, azimuth and elevation). Asrepresented by block 342, input to sequence 340 is a set of fast timesamples for each chirp in the frame, and for each receive (Rx) channel.For the purposes of this example, it is assumed that there are 16 Rxchannels, and that each frame includes 512 chirps, of which 256 areuniform FMCW chirps interleaved with 256 non-uniform FMCW chirps havingchirp profiles differing by starting frequency and repetition interval.Moreover, each chirp is represented by 256 samples, so the number offast time samples processed for each frame in this implementation wouldbe 256×512×16=786,432.

In block 344, fast time windowing and range transformations using lowercomputational overhead FFT operations are performed for all chirps andall Rx channels to generate coarse resolution range parameters, and thenin block 346, MIMO demodulation is performed. From this MIMOdemodulation, two data cubes, a uniform data cube 348 and a non-uniformdata cube 350, may be generated. While in some implementations, thenon-uniform data cube could also include uniform chirps from uniformantenna arrays, in the illustrated implementation, the uniform data cubeincludes only uniform chirps from uniform antenna arrays and thenon-uniform data cube includes only non-uniform chirps from sparseantenna arrays.

Next, in block 352, Doppler transformations using lower computationaloverhead FFT operations are performed on the uniform data cube, and onall uniform virtual channels, and in block 354, beamformingtransformations using lower computational overhead FFT operations areperformed on the uniform data cube, and on all uniform virtual channels.It will be appreciated that both of these blocks will generally maintaindesired Doppler/angle resolution, but will also introduce Doppler/angleambiguities.

Next, in block 356, potential or candidate objects are detected from theuniform data cube, e.g., by thresholding each cell, and the potentialobjects may include cells meeting the threshold, and in some instances,one or more neighboring cells to each detected cell, resulting in a setof selected cells from the uniform data cube representing the potentialobjects. Control then passes to block 358 to perform a finer rangecalculation on these selected cells, e.g., compensating phase variationalong the slow time due to carrier frequency variation.

Then, in block 360, Doppler disambiguation is performed using highercomputation overhead Doppler transformations such as Doppler DFToperations and thereby resolve the Doppler ambiguities introduced in theuniform data cube. Likewise, in block 362, beamforming disambiguation isperformed using higher computation overhead beamforming transformationssuch as beamforming DFT operations and thereby resolve the angleambiguities introduced in the uniform data cube.

Then, in block 364, finer range and Doppler/angle ambiguity detection isperformed based upon the calculations performed in blocks 358-362,resulting in the output of a set of objects, along with range, Doppler,elevation angle and azimuth angle parameters, which in someimplementations, may be formatted into a point cloud 366.

It will therefore be appreciated that enhanced radar performance may beobtained through the use of non-uniform FMCW chirps, and with asubstantial reduction in computational overhead in some implementations.As an example, consider a 4D imaging radar sensor for use in anautomotive application, where it is desirable to support a range of 300m with 0.15 m resolution, a velocity of +/−76.8 m/s with an 0.1 m/sresolution, an azimuth angle of +/−50 degrees with a 1 degree resolutionand an elevation angle of +/−15 degrees with a 1 degree resolution. Sucha range may be met using a 1 GHz bandwidth and 256×8 samples per chirp,and such a velocity may be met using 512×3 chirps and a 19.5 ms frameduration. The azimuth angle may be met by a 20 cm virtual aperture with100 horizontal channels while the elevation angle may be met by a 20 cmvirtual aperture with 30 vertical channels.

Using a conventional approach, the total number of 4D cells that wouldneed to be calculated in order to meet these requirements would be(256×8)×(512×3)×100×30=9.4e9 cells per frame. In contrast, using the twostage disambiguation approach discussed above, the same requirements maybe met with substantially reduced processing overhead. Assuming 96virtual channels for each data cube, the number of 4D cells that wouldneed to be calculated using the above sequence of operations would be(256×256×16×16)+((8×3×7×3)×#selected_cells)), assuming that the rangeupsampling factor for finer range bin calculation is 8, 3 ambiguouscandidates per detected doppler, 7 ambiguous candidates per detectedazimuth angle, and 3 ambiguous candidates per detected elevation angle.Assuming that the first stage results in a reasonable number of selectedcells such as 5000, the total number of 4D cells that would need to becalculated would be 1.9e7 cells per frame, which is roughly 0.2% of thenumber required from a conventional approach, while still maintainingcomparable parameter resolutions for the identified objects.

Other variations will be apparent to those of ordinary skill. Therefore,the invention lies in the claims hereinafter appended.

What is claimed is:
 1. A radar sensor for a vehicle, comprising: a radartransmitter configured to transmit a first radar signal, the first radarsignal including a frame associated with a plurality of frequencymodulated continuous wave (FMCW) chirps, wherein the frame is a coherentprocessing interval, wherein the plurality of FMWC chirps includes aplurality of uniform FMCW chirps having a particular chirp profile and aplurality of non-uniform FMCW chirps having second chirp profiles; aradar receiver configured to receive a second radar signal that is areflected signal of the first radar signal; and a control logic coupledto the first radar receiver and configured to process the second radarsignal, based on the uniform and non-uniform FMCW chirps in the frame,to determine one or more parameters of an object in a field of view ofthe radar transmitter.
 2. The radar sensor of claim 1, wherein thesecond chirp profiles of the plurality of non-uniform FMCW chirps differfrom one another and from the particular chirp profile of the pluralityof uniform FMWC chirps based at least upon differing starting frequencyand repetition interval.
 3. The radar sensor of claim 1, wherein thechirp profiles of the FMCW chirps further differ based upon chirpduration or chirp slope.
 4. The radar sensor of claim 1, wherein theuniform FMCW chirps and the non-uniform FMCW chirps are interleaved withone another such that the frame includes alternating uniform andnon-uniform FMCW chirps.
 5. The radar sensor of claim 1, wherein thecontrol logic uses the uniform and non-uniform FMCW chirps in the frameto sense the one or more parameters of the object by: generating auniform data cube by performing a range transformation with fast-timesamples of the second radar signal and using the uniform FMCW chirps;and detecting a plurality of candidate objects in the uniform data cube.6. The radar sensor of claim 5, wherein the control logic further usesthe non-uniform FMCW chirps in the frame to sense the one or moreparameters of the object by: generating a non-uniform data cube byperforming a range transformation with fast-time samples of the secondradar signal and using the non-uniform FMCW chirps; and enhancing rangeresolution for at least a subset of the plurality of candidate objectsusing the non-uniform data cube.
 7. The radar sensor of claim 5, whereinthe control logic further uses the non-uniform FMCW chirps in the frameto sense the one or more parameters of the object by: generating anon-uniform data cube by performing a range transformation withfast-time samples of the second radar signal and using the non-uniformFMCW chirps; and performing a Doppler transformation with thenon-uniform data cube to resolve Doppler ambiguity in at least a subsetof the plurality of candidate objects.
 8. The radar sensor of claim 7,wherein the control logic further uses the non-uniform FMCW chirps inthe frame to sense the one or more parameters of the object by:performing a Doppler transformation with the uniform data cube togenerate Doppler parameters for the plurality of candidate objects;wherein performing the Doppler transformation with the uniform data cubeintroduces Doppler ambiguity in the uniform data cube; and whereinperforming the Doppler transformation with the non-uniform data cuberesolves the Doppler ambiguity introduced in the uniform data cube. 9.The radar sensor of claim 8, wherein the Doppler transformationperformed with the uniform data cube comprises a Fast Fourier Transform(FFT) transformation and the Doppler transformation performed with thenon-uniform data cube comprises a Discrete Fourier Transform (DFT)transformation.
 10. The radar sensor of claim 5, wherein the controllogic further uses the non-uniform FMCW chirps in the frame to sense theone or more parameters of the object by: generating a non-uniform datacube by performing a range transformation with fast-time samples of thesecond radar signal and using the non-uniform FMCW chirps; andperforming a beamforming transformation with the non-uniform data cubeto resolve angle ambiguity in at least a subset of the plurality ofcandidate objects in the uniform data cube.
 11. The radar sensor ofclaim 10, wherein the control logic further uses the non-uniform FMCWchirps in the frame to sense the one or more parameters of the objectby: performing a beamforming transformation with the uniform data cubeto generate angle parameters for the plurality of candidate objects;wherein performing the beamforming transformation with the uniform datacube introduces angle ambiguity in the uniform data cube; and whereinperforming the beamforming transformation with the non-uniform data cuberesolves the angle ambiguity introduced in the uniform data cube. 12.The radar sensor of claim 11, wherein the beamforming transformationperformed with the uniform data cube comprises a Fast Fourier Transform(FFT) transformation and the beamforming transformation performed withthe non-uniform data cube comprises a Discrete Fourier Transform (DFT)transformation.
 13. The radar sensor of claim 1, wherein the chirpprofiles of the non-uniform FMCW chirps differ based upon startingfrequency such that a total frequency band of the frame is split into aplurality of sub-bands defined by the non-uniform FMCW chirps, andwherein the control logic uses the non-uniform FMCW chirps in the frameto sense the one or more parameters of the object by subsampling onrange within the total frequency band of the frame.
 14. The radar sensorof claim 1, wherein the control logic uses the non-uniform FMCW chirpsin the frame to sense the one or more parameters of the object by subsampling on Doppler over a duration of the frame.
 15. The radar sensorof claim 1, wherein the radar transmitter is a multiple input multipleoutput (MIMO) radar transmitter including a plurality of transmitchannels and the radar receiver is a MIMO radar receiver including aplurality of receive channels, wherein the first radar signal isgenerated for a first transmit channel of the plurality of transmitchannels and the second radar signal is received by a first receivechannel of the plurality of receive channels.
 16. An autonomous vehiclecontrol system, comprising: a radar transmitter configured to transmit afirst radar signal, the first radar signal including a frame associatedwith a plurality of frequency modulated continuous wave (FMCW) chirps,wherein the frame is a coherent processing interval, wherein theplurality of FMWC chirps includes a plurality of uniform FMCW chirpshaving a particular chirp profile and a plurality of non-uniform FMCWchirps having second chirp profiles; a radar receiver configured toreceive a second radar signal that is a reflected signal of the firstradar signal; and a control logic coupled to the radar receiver andconfigured to process the second radar signal, based on the uniform andnon-uniform FMCW chirps in the frame, to determine one or moreparameters of an object in a field of view of the radar transmitter. 17.The autonomous vehicle control system of claim 16, wherein the secondchirp profiles of the plurality of non-uniform FMCW chirps differ fromone another and from the particular chirp profile of the plurality ofuniform FMWC chirps based at least upon differing starting frequency andrepetition interval.
 18. The autonomous vehicle control system of claim16, wherein the radar transmitter is a multiple input multiple output(MIMO) radar transmitter including a plurality of transmit channels andthe radar receiver is a MIMO radar receiver including a plurality ofreceive channels, wherein the first radar signal is generated for afirst transmit channel of the plurality of transmit channels and thesecond radar signal is received by a first receive channel of theplurality of receive channels.
 19. An autonomous vehicle, comprising: apowertrain configured to move the autonomous vehicle; and an autonomousvehicle control system configured to operate the powertrain, theautonomous vehicle control system including: a radar transmitterconfigured to transmit a first radar signal, the first radar signalincluding a frame associated with a plurality of frequency modulatedcontinuous wave (FMCW) chirps, wherein the frame is a coherentprocessing interval, wherein the plurality of FMWC chirps includes aplurality of uniform FMCW chirps having a particular chirp profile and aplurality of non-uniform FMCW chirps having second chirp profiles; aradar receiver configured to receive a second radar signal that is areflected signal of the first radar signal; and a control logic coupledto the radar receiver and configured to process the second radar signal,based on the uniform and non-uniform FMCW chirps in the frame, todetermine one or more parameters of an object in a field of view of theradar transmitter.
 20. The autonomous vehicle of claim 19, wherein thesecond chirp profiles of the plurality of non-uniform FMCW chirps differfrom one another and from the particular chirp profile of the pluralityof uniform FMWC chirps based at least upon differing starting frequencyand repetition interval.